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Assessing the capabilities of the Surface Water and Ocean Topography (SWOT) mission for large lake water surface elevation monitoring under different wind conditions

机译:在不同风力条件下评估大湖水面升高监测的地表水和海洋地形(SWOT)任务的能力

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Lakes are important sources of freshwater and provide essential ecosystem services. Monitoring their spatial and temporal variability, and their functions, is an important task within the development of sustainable water management strategies. The Surface Water and Ocean Topography (SWOT) mission will provide continuous information on the dynamics of continental (rivers, lakes, wetlands and reservoirs) and ocean water bodies. This work aims to contribute to the international effort evaluating the SWOT satellite (2022 launch) performance for water balance assessment over large lakes (e.g., 100 ?km 2 ). For this purpose, a hydrodynamic model was set up over Mamawi Lake, Canada, and different wind scenarios on lake hydrodynamics were simulated. The derived water surface elevations (WSEs) were compared to synthetic elevations produced by the Jet Propulsion Laboratory (JPL) SWOT high resolution (SWOT-HR) simulator. Moreover, water storages and net flows were retrieved from different possible SWOT orbital configurations and synthetic gauge measurements. In general, a good agreement was found between the WSE simulated from the model and those mimicked by the SWOT-HR simulator. Depending on the wind scenario, errors ranged between approximately ?2 and 5?cm for mean error and from 30 to 70?cm root mean square error. Low spatial coverage of the lake was found to generate important biases in the retrievals of water volume or net flow between two satellite passes in the presence of local heterogeneities in WSE. However, the precision of retrievals was found to increase as spatial coverage increases, becoming more reliable than the retrievals from three synthetic gauges when spatial coverage approaches 100?%, demonstrating the capabilities of the future SWOT mission in monitoring dynamic WSE for large lakes across Canada.
机译:湖泊是淡水的重要来源,提供必要的生态系统服务。监测其空间和时间可变性及其功能,是可持续水管理策略发展中的重要任务。地表水和海洋地形(SWOT)任务将提供有关大陆(河流,湖泊,湿地和水库)和海洋水体的动态的持续信息。这项工作旨在促进评估水平卫星的国际努力(2022年发布)对大型湖泊的水平评估(例如,& 100?Km 2)。为此目的,建立了一个流体动力学模型,在加拿大Mamawi Lake,并模拟了湖泊流体动力学的不同风景。将衍生的水表面升高(WSES)与喷射推进实验室(JPL)SWOT高分辨率(SWOT-HR)模拟器产生的合成升高进行比较。此外,从不同可能的SWOT轨道配置和合成计测量中检索水储存和净流量。通常,从模型模拟的WSE和由SWOT-HR模拟器模拟的人之间发现了良好的一致性。根据风景,误差之间的误差范围为2和5?cm,用于平均误差,从30到70?cm根均方误差。发现湖泊的低空间覆盖率在WSE局部异质性存在下,在水量检索或两颗卫星之间的净流动中产生重要偏见。然而,当空间覆盖范围增加时,检索的精度增加增加,当空间覆盖方法100?%时,越来越可靠,从三个合成仪中的检索越来越可靠,展示了未来SWOT任务监控加拿大大湖泊动态WSE的能力。

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